Exploration of Vitamin B6-Based Redox-Active Pyridinium Salts Towards the Application in Aqueous Organic Flow Batteries.

Pyridoxal hydrochloride, a vitamin B6 vitamer, was synthetically converted to a series of diverse redox-active benzoyl pyridinium salts. Cyclic voltammetry studies demonstrated redox reversibility under basic conditions, and two of the most promising salts were subjected to laboratory-scale flow battery tests involving galvanostatic cycling at 10 mM in 0.1 M NaOH. In these tests, the battery was charged completely, corresponding to the transfer of two electrons to the electrolyte, but no discharge was observed. Both CV analysis and electrochemical simulations confirmed that the redox wave observed in the experimental voltammograms corresponds to a two-electron process. To explain the irreversibility in the battery tests, we conducted bulk electrolysis with the benzoyl pyridinium salts, affording the corresponding benzylic secondary alcohols. Computational studies suggest that the reduction proceeds in three consecutive steps: first electron transfer (ET), then proton-coupled electron transfer (PCET) and finally proton transfer (PT) to give the secondary alcohol. 1H NMR deuterium exchange studies indicated that the last PT step is not reversible in 0.1 M NaOH, rendering the entire redox process irreversible. The apparent reversibility observed in CV at the basic media likely arises from the slow rate of the PT step at the timescale of the measurement.

Kinetics of N2 Release from Diazo Compounds: A Combined Machine Learning-Density Functional Theory Study.

Diazo compounds are commonly employed as carbene precursors in carbene transfer reactions during a variety of functionalization procedures. Release of N2 gas from diazo compounds may lead to carbene formation, and the ease of this process is highly dependent on the characteristics of the substituents located in the vicinity of the diazo moiety. A quantum mechanical density functional theory assisted by machine learning was used to investigate the relationship between the chemical features of diazo compounds and the activation energy required for N2 elimination. Our results suggest that diazo molecules, possessing a higher positive partial charge on the carbene carbon and more negative charge on the terminal nitrogen, encounter a lower energy barrier. A more positive C charge decreases the π-donor ability of the carbene lone pair to the π* orbital of N2, while the more negative N charge is a result of a weak interaction between N2 lone pair and vacant p orbital of the carbene. The findings of this study can pave the way for molecular engineering for the purpose of carbene generation, which serves as a crucial intermediate for many chemical transformations in synthetic chemistry.

Density functional theory and machine learning for electrochemical square-scheme prediction: an application to quinone-type molecules relevant to redox flow batteries.

Proton-electron transfer (PET) reactions are rather common in chemistry and crucial in energy storage applications. How electrons and protons are involved or which mechanism dominates is strongly molecule and pH dependent. Quantum chemical methods can be used to assess redox potential (Ered.) and acidity constant (pKa) values but the computations are rather time consuming. In this work, supervised machine learning (ML) models are used to predict PET reactions and analyze molecular space. The data for ML have been created by density functional theory (DFT) calculations. Random forest regression models are trained and tested on a dataset that we created. The dataset contains more than 8200 quinone-type organic molecules that each underwent two proton and two electron transfer reactions. Both structural and chemical descriptors are used. The HOMO of the reactant and LUMO of the product participating in the oxidation reaction appeared to be strongly associated with Ered.. Trained models using a SMILES-based structural descriptor can efficiently predict the pKa and Ered. with a mean absolute error of less than 1 and 66 mV, respectively. Good prediction accuracy of R2 > 0.76 and >0.90 was also obtained on the external test set for Ered. and pKa, respectively. This hybrid DFT-ML study can be applied to speed up the screening of quinone-type molecules for energy storage and other applications.

Understanding Electron Transfer Reactions Using Constrained Density Functional Theory: Complications Due to Surface Interactions.

The kinetic rates of electrochemical reactions depend on electrodes and molecules in question. In a flow battery, where the electrolyte molecules are charged and discharged on the electrodes, the efficiency of the electron transfer is of crucial importance for the performance of the device. The purpose of this work is to present a systematic atomic-level computational protocol for studying electron transfer between electrolyte and electrode. The computations are done by using constrained density functional theory (CDFT) to ensure that the electron is either on the electrode or in the electrolyte. The ab initio molecular dynamics (AIMD) is used to simulate the movement of the atoms. We use the Marcus theory to predict electron transfer rates and the combined CDFT-AIMD approach to compute the parameters for the Marcus theory where it is needed. We model the electrode with a single layer of graphene and methylviologen, 4,4'-dimethyldiquat, desalted basic red 5, 2-hydroxy-1,4-naphthaquinone, and 1,1-di(2-ethanol)-4,4-bipyridinium were selected for the electrolyte molecules. All of these molecules undergo consecutive electrochemical reactions with one electron being transferred at each stage. Because of significant electrode-molecule interactions, it is not possible to evaluate outer-sphere ET. This theoretical study contributes toward the development of a realistic-level prediction of electron transfer kinetics suitable for energy storage applications.

Chlorine doping of MoSe2 flakes by ion implantation.

The efficient integration of transition metal dichalcogenides (TMDs) into the current electronic device technology requires mastering the techniques of effective tuning of their optoelectronic properties. Specifically, controllable doping is essential. For conventional bulk semiconductors, ion implantation is the most developed method offering stable and tunable doping. In this work, we demonstrate n-type doping in MoSe2 flakes realized by low-energy ion implantation of Cl+ ions followed by millisecond-range flash lamp annealing (FLA). We further show that FLA for 3 ms with a peak temperature of about 1000 °C is enough to recrystallize implanted MoSe2. The Cl distribution in few-layer-thick MoSe2 is measured by secondary ion mass spectrometry. An increase in the electron concentration with increasing Cl fluence is determined from the softening and red shift of the Raman-active A1g phonon mode due to the Fano effect. The electrical measurements confirm the n-type doping of Cl-implanted MoSe2. A comparison of the results of our density functional theory calculations and experimental temperature-dependent micro-Raman spectroscopy data indicates that Cl atoms are incorporated into the atomic network of MoSe2 as substitutional donor impurities.

Hydrogen-assisted post-growth substitution of tellurium into molybdenum disulfide monolayers with tunable compositions.

Herein we report the successful doping of tellurium (Te) into molybdenum disulfide (MoS2) monolayers to form MoS2x Te2(1-x) alloy with variable compositions via a hydrogen-assisted post-growth chemical vapor deposition process. It is confirmed that H2 plays an indispensable role in the Te substitution into as-grown MoS2 monolayers. Atomic-resolution transmission electron microscopy allows us to determine the lattice sites and the concentration of introduced Te atoms. At a relatively low concentration, tellurium is only substituted in the sulfur sublattice to form monolayer MoS2(1-x)Te2x alloy, while with increasing Te concentration (up to ∼27.6% achieved in this study), local regions with enriched tellurium, large structural distortions, and obvious sulfur deficiency are observed. Statistical analysis of the Te distribution indicates the random substitution. Density functional theory calculations are used to investigate the stability of the alloy structures and their electronic properties. Comparison with experimental results indicate that the samples are unstrained and the Te atoms are predominantly substituted in the top S sublattice. Importantly, such ultimately thin Janus structure of MoS2(1-x)Te2x exhibits properties that are distinct from their constituents. We believe our results will inspire further exploration of the versatile properties of asymmetric 2D TMD alloys.